A report by Alistair Ritchie.
On August 16 and 17 the National Land Resource Centre hosted a trans-Tasman soil information workshop at the Landcare Research office in Wellington. The workshop followed a one day joint soil and geology information modelling workshop at GNS Science Lower Hutt.
These workshops are typical of a growing community of environmental and information scientists that has been collaborating to develop standardised ways of storing and sharing data. Key to this are well defined information models describing scientific phenomena that can be subsequently adapted to define the structure of the digital datasets. Sharing land and soil information in a standardised way can bring many benefits: it increases the efficiency of data management and exchange by reducing the number of file formats and data structures users must deal with; it allows the integration of data from disparate data sources; and, by focussing on core land and soil concepts rather than one-off user interfaces, it increases the likelihood that the data may be reused for multiple, unforeseen, purposes.
This work is increasingly important as environmental science makes extensive use of computational models that combine data describing a variety of phenomena from a variety of sources. These models may be run on desktop computers or across interconnected computing facilities using and producing very large volumes of data. This increasing scale of operation – often called the ‘data deluge’ – means that data acquisition and exchange is becoming more and more expensive. It is vital that we reduce the time spent exchanging and manipulating data, allowing more time to do the actual analysis.
The resulting datasets, delivered using internet technology, can be used for any number of applications, ranging from environmental research, economic and land use modelling, to the management of farmland.
When building these information models it is helpful to not only address the data from the perspective of an individual discipline, say soil science, but also from the those that describe related systems (geology, hydrology and so on). This improves the ability to integrate and compare data collected by different scientists, but also to reduces the amount of time spent developing the models by sharing models for common concepts.
With this in mind, Landcare Research and CSIRO Land and Water took the opportunity to conduct a joint soil and geology information workshop with members of the International Union of Geological Sciences (IUGS) geology information working group as they met at GNS Science, Lower Hutt. The geologists have spent the last ten years developing the GeoScience Mark-up Language (GeoSciML) – a web-oriented data model for the exchange of geology data and the driver for projects such as the OneGeology digital map of the world geology (http://onegeology.org/), and earth science data infrastructures in Australia, the US, Canada and Europe.
The one day workshop (attended by Landcare Research staff) covered how the two groups used one another’s data and identified a great deal of common ground, considering shared technology and integration options in their information models (not just covering the physical phenomena, but also describing observation and sampling activities, and the use of technical vocabularies). It is clear that the emerging soil information community can learn a lot from the geology communities successes (and mistakes!) while the soil community can teach the geologists a lot about describing quantitative data and the related uncertainty.
Immediately after this workshop, the Landcare Research and CSIRO attendees attended a National Land Resource Centre sponsored soil information modelling meeting. Here work began on an Oceania SoilML, the soil equivalent of GeoSciML, and a related information model for the GlobalSoilMap.net (http://globalsoilmap.net/) project. To ensure that we didn’t reinvent the wheel, the meeting considered models that have been developed in Australia and Europe, particularly a draft International Standards Organisation (ISO) Soil Data Quality standard. While the group found the ISO standard to have merit, especially when blended with the Australian model, a number of issues were identified and these have been submitted to ISO via the Australian standards body. Meanwhile, the GlobalSoilMap.net model – developed by Landcare Research – was agreed to be a viable candidate as an international standard. This model, and a web interface demonstrating the exploration of the data, will be demonstrated to an Oceania GSM meeting in October.
This work will also have direct application to research Landcare Research is presently engaged in. The Oceania SoilML information model will be used to inform the development of a new model for the ideal content of the New Zealand National Soils Database – potentially saving many months of development time.
Both workshops were a great success. They identified scope for collaboration between the geology and soil communities, allowing both to effectively share technical and intellectual resources. Meanwhile, the development of a SoilML can be considered a more tractable exercise, benefiting already from preceding work, and clear points of contact with GeoSciML. The challenge now is to extend the effort beyond Oceania and formally integrate the information modelling work into activities of the International Union of Soil Sciences (IUSS) Soil Information Working Group.